Designing accountable systems

Severin Kacianka, Alexander Pretschner

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

19 Scopus citations

Abstract

Accountability is an often called for property of technical systems. It is a requirement for algorithmic decision systems, autonomous cyber-physical systems, and for software systems in general. As a concept, accountability goes back to the early history of Liberalism and is suggested as a tool to limit the use of power. This long history has also given us many, often slightly differing, definitions of accountability. The problem that software developers now face is to understand what accountability means for their systems and how to reflect it in a system's design. To enable the rigorous study of accountability in a system, we need models that are suitable for capturing such a varied concept. In this paper, we present a method to express and compare different definitions of accountability using Structural Causal Models. We show how these models can be used to evaluate a system's design and present a small use case based on an autonomous car.

Original languageEnglish
Title of host publicationFAccT 2021 - Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency
PublisherAssociation for Computing Machinery, Inc
Pages424-437
Number of pages14
ISBN (Electronic)9781450383097
DOIs
StatePublished - 3 Mar 2021
Event4th ACM Conference on Fairness, Accountability, and Transparency, FAccT 2021 - Virtual, Online, Canada
Duration: 3 Mar 202110 Mar 2021

Publication series

NameFAccT 2021 - Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency

Conference

Conference4th ACM Conference on Fairness, Accountability, and Transparency, FAccT 2021
Country/TerritoryCanada
CityVirtual, Online
Period3/03/2110/03/21

Keywords

  • Accountability
  • Socio-Technical Systems
  • Structural Causal Models

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